Described below is a method for reducing noise for coding of noisy images or image sequences.
Professional video applications such as monitoring systems for buildings, industrial manufacturing and medical applications need video signals with very high quality. These signals are likely to have very high resolutions in spatial as well as temporal direction, so the uncompressed data can become very large. It is therefore important to compress these signals as much as possible without visible information loss. Recent video compression systems exploit the temporal correlation between images, but they are optimized for consumer quality applications.
Usually, image sequences that are acquired by a physical process can be considered to be degraded by noise caused through the acquisition process. Noise might result from sensor noise, amplifier noise or quantization noise, and so on. It has been found that at very high quality so-called inter-frame coding becomes less efficient relative to so-called intra-frame coding. An inter-frame is a frame in a video compression stream which is expressed in terms of one or more neighbouring frames. The “inter” part of the term refers to the use of inter-frame prediction. This kind of prediction tries to take advantage from temporal redundancy between neighbouring frames in order to achieve higher compression rates. The term intra-frame coding refers to the fact that the various lossless and lossy compression techniques are performed relative to information that is contained only within the current frame and not relative to any other frame in the video sequence. In other words, no temporal processing is performed outside of the current picture or frame. It is expected that the reason for the different efficiencies of inter- and intra-frame coding is (additive) noise within a video signal which effects the motion compensated prediction inside a video encoder/decoder.
In order to improve the coding efficiency, different algorithms can be applied to the noisy image sequences prior to encoding.
The noise pre-filtering can be done inside the video encoder. Thus, the bitrate for coding a noisy image sequence is reduced while its subjective quality is improved. However, the filtering process introduces errors, which is not allowed in lossless compression of video signals.
Another approach for bitrate reduction is in-loop filtering of lossy encoded video data. In lossy coding a deblocking filter or quantization noise removal filter can improve the coding efficiency as well as the visual quality of the signal. An in-loop denoising filter for reduction of impulse noise leads to a bitrate reduction and subjective quality improvement.